Score-Based Generative Modeling without Diffusion: Langevin MCMC All the Way

Score-based generation need not reverse a forward diffusion process. This talk presents an alternative based on Langevin MCMC at a fixed noise level, with effective noise falling as measurements accumulate. Suitable noise choices keep the sampling problems log-concave, and extensions connect the construction to discrete-data generation.